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In this study, we concentrate on the seismic signature of subducted sediments and suggest the formation of the L‐discontinuity beneath the ancient craton related to migrated sediment dehydration. We first determined the single‐crystal elasticity of topaz, the product of sediment dehydration, at high pressures and temperatures by Brillouin scattering. Using the derived elastic parameters, we establish the velocity and density profiles of subducted sediments in the upper mantle. According to our modeling results, 8.5–17.5 vol.% sediments intruding into the upper mantle will induce a 2%–4% low‐VS anomaly at 210–260 km. Meanwhile, continuous heating will lead to the dehydration of phengite in sediments. The dehydration of this amount sediments can generate a 3%–6% ISS with negative Clapeyron slopes, satisfying the observed L‐discontinuity in northern Finland and northern America without the anisotropy changes but accompanied by low‐velocity anomalies. Our study thus provides new insights into the origin of the L‐discontinuity. Plain Language Summary: The origin of the global seismic discontinuities in the Earth's mantle has been well understood, but the formation mechanism of some local seismic discontinuities is still vague. Lehmann discontinuity (L‐discontinuity) is one of the regional discontinuities in the upper mantle with a 2%–6% impendence contrast (ISS) and negative Clapeyron slope. However, the deformation mechanism changes of olivine cannot explain the formation of the L‐discontinuity without the anisotropy changes. Here, we emphasize the significance of the migration and dehydration of the subducted sediments in the origin of the L‐discontinuity beneath the ancient craton. We determined the single‐crystal elasticity of topaz, the product of the sediment dehydration, and then investigated the seismic signature of subducted sediments. Our modeling results indicated that ∼17.5 vol.% sediments intruding into the upper mantle would lead to ∼4% low‐VS anomalies at 210–260 km. After the continuous heating, these intruding sediments would dehydrate by the reaction with the negative Clapeyron slopes, thus producing significant ISS. Therefore, the migration and dehydration of the subducted sediments can reasonably interpret the seismic characteristics of the L‐discontinuity beneath the cratonic regions such as northern Finland and northern America. Our results deepen the understanding of the origin of the L‐discontinuity. Key Points: Single‐crystal elasticity of topaz under high pressure and temperature has been investigated by Brillouin scatteringThe obtained elasticity parameters are used to model the density and velocity profiles of the subducted sedimentsWe suggest the formation of the L‐discontinuity beneath the ancient craton related to migrated sediment dehydration [ABSTRACT FROM AUTHOR]

This study investigated two random forest (RF) models for the non‐iterative parametrization of surface‐layer turbulent fluxes: (a) the RF scheme, a calculation model that is directly trained using correlated variables, and (b) the RF_Li10 scheme, a random forest correction model based on the Li10 scheme (Li et al., 2010, https://doi.org/10.1007/s10546-010-9523-y). A comparison between these two new models and the Li10 scheme against an iterative scheme revealed the hierarchy of maximum relative errors in estimating stability parameters, as well as momentum and heat transfer coefficients. This hierarchy is as follows: the Li10 scheme is the greatest, followed by the RF scheme, with the RF_Li10 scheme exhibiting the least errors. Plain Language Summary: The computation module for surface‐layer turbulent fluxes is an essential component of numerical weather prediction models. Based on the Monin‐Obukhov Similarity Theory, many parameterization schemes for surface fluxes have been proposed. With the advancement of artificial intelligence, machine learning methods have been applied in meteorology. This study applies the RF model in machine learning to the parametrization of surface‐layer turbulent fluxes. The RF scheme directly calculates the stability parameter after training, and the RF_Li10 scheme is designed to refine the stability parameter derived from the Li10 scheme, by utilizing the RF algorithm for this correction process. In addition, the two new schemes have also been used to calculate the momentum and heat transfer coefficients. The values calculated from the Li10 scheme, RF scheme, and RF_Li10 scheme are compared with the values calculated from the iterative scheme. Under different surface roughness conditions, the average relative errors of the stability parameter obtained from the Li10 scheme, RF scheme, and RF_Li10 scheme are 3.17%, 3.42%, and 0.17%, respectively; the maximum average relative errors of the stability parameter are 5.67%, 3.52%, and 0.52% respectively. Key Points: Two Random Forest models (RF and RF_Li10) for the non‐iterative parametrization of near‐surface turbulent fluxes are proposedCompared to the iterative schemes and existing parameterization schemes, the RF_Li10 scheme exhibits the lowest calculation errorCompared to the iterative schemes, the RF scheme and RF_Li10 scheme reduce the computation time by 91.0% and 78.4%, respectively [ABSTRACT FROM AUTHOR]